1. Field of the Invention
The present invention relates to a method for updating a legend of a spatial display for use with graphical user interface of a field computer linked to one or more sensors for sensing data or information from a piece of equipment performing an agricultural operation. In particular, to a method for real-time calculation and regeneration of a legend display for a spatial map.
2. Background
Agriculture, like most fields, has been technologically transformed in recent years. The field of precision agriculture is one such area of technological innovation that has produced far-reaching consequences and affects for modern agriculture. Advances in crop management, and in particular, the management of within-field variation creates enormous benefits and challenges for site-specific farming and crop management.
Presently, crop management decisions are typically made on a within-field basis. Entire fields are no longer treated as if they were one homogeneous unit. It has been understood for a long time that soil characteristics (pH, texture, organic matter) and other factors such as moisture conditions or weed problems may vary considerably within a given field. In the past it was not technologically feasible to account and track for such localized variations. This is no longer the case. Instead of managing an entire farm or field based upon some hypothetical average condition, which may not exist anywhere, a precision farming approach recognizes site-specific differences within fields and adjusts management actions accordingly. For example, based on extensive soil testing, different locations within a field may receive different amounts of fertilizer.
Technological advancements make precision farming not only possible, but make it easier. Smaller, faster, less expensive computers are of critical importance in gathering, analyzing, and acting upon information about soils and growing conditions in a timely manner. Soil sensors, variable rate applicators, on-the-go yield monitors, and global positioning systems (GPS) that use satellite technology to identify specific locations within fields are the high-tech tools of the precision farmer.
Harnessing this wealth of technology requires sophisticated data collection and analysis tools, of a type not considered practical or possible a few years ago. Accordingly, prior art methods of collection and analysis of crop management information are antiquated when it comes to meeting the demands of precision farming. Much improvement is required when it comes to managing the wealth of data available in modern farming in order to realize the true potential of precision agriculture.
In particular, present agricultural monitors, such as yield monitors and the like, display on a continuous basis data values received from single or multiple sensors located on an agricultural machine. Systems that can handle instantaneous measured and calculated data values are referred to as real-time monitoring systems.
Systems that have the capability to record data values received from single or multiple sensors on a machine on a continuous basis are referred to as field computers. When a field computer is coupled to a global positioning system, the latitude, longitude, and elevation can be recorded with each data value at the geographic location where the value was measured.
Recorded geographic position can be used to plot a spatial representation of the data in the form of a map for display on the computing device. The map can further convey spatial information by associating a grayscale or color with points on the map, wherein the grayscale or color represents a unique data value spatially associated with a particular geographic point represented on the map. However, when there are many unique values, it becomes impractical assign a unique color to each unique value and furthermore becomes difficult for the user to interpret the information as the number of different colors overwhelms the resolution of the screen displaying the map. Grouping segments of data values into a plurality of ranges, and displaying a unique grayscale or color for all points that fall within a given range is the normal method of dealing with this problem. This reduces the number of colors required to a manageable level, without unreasonably restricting the amount of information that the map can convey.
In order to understand the grayscale/color scheme, mapping systems typically display a legend to describe the data grouping displayed on the map. The legend displays a color indicator along with the corresponding range of values that are associated with that color on the map. In principle, the legend is merely an interpretive aid used to help distinguish the colors used to convey a spatial representation of actual information. In practice, due to the limitations of both the computer systems and the resolution of display screens associated therewith, the legend typically drives how the map is drawn. This is especially true in real-time systems.
For real-time systems data collection and presentation is on going, which requires frequent updating of the screen to reflect new data. Field computers can plot a gray-scale or color map of recorded sensor data, and utilize a legend to assist the user in interpreting the map. When data recording is in progress, the field computer is continuously adding new data to the map. These systems are referred to as “real-time” mapping systems. Present real-time mapping systems do not have the computational power to continuously update the legend data groupings and map to best represent the data. These systems use a legend based on fixed or user-defined ranges, which do not change dynamically during the data collection operation. With this method, the user must either continuously monitor the data map and manually adjust the legend as the data is collected in order to adjust the data groupings to ensure the presentation is meaningful, or ignore the system which will quickly render the data presentation meaningless. Furthermore, frequent adjustments to the legend data groupings require the computer to constantly regenerate the map, which can take a great deal of computational time. In addition, the user is typically operating the equipment at the same time and cannot afford unnecessary distractions.
Thus, a need exists for an improved method for a real-time field computer to monitor the changes in the data and make adjustments to the map legend on a much more intentional, efficient, and predictable basis without input from the user.